Journal of
Systemics, Cybernetics and Informatics
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ISSN: 1690-4524 (Online)


Peer Reviewed Journal via three different mandatory reviewing processes, since 2006, and, from September 2020, a fourth mandatory peer-editing has been added.

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Published by
The International Institute of Informatics and Cybernetics


Re-Published in
Academia.edu
(A Community of about 40.000.000 Academics)


Honorary Editorial Advisory Board's Chair
William Lesso (1931-2015)

Editor-in-Chief
Nagib C. Callaos


Sponsored by
The International Institute of
Informatics and Systemics

www.iiis.org
 

Editorial Advisory Board

Quality Assurance

Editors

Journal's Reviewers
Call for Special Articles
 

Description and Aims

Submission of Articles

Areas and Subareas

Information to Contributors

Editorial Peer Review Methodology

Integrating Reviewing Processes


Utilization of Artificial Intelligence by Students in Interdisciplinary Field of Biomedical Engineering
Shigehiro Hashimoto
(pages: 1-5)

Transdisciplinary Applications of Data Visualization and Data Mining Techniques as Represented for Human Diseases
Richard S. Segall
(pages: 6-15)

Beyond Status Quo: Why is Transdisciplinary Communication Instrumental in Innovation?
James Lipuma, Cristo Leon
(pages: 16-20)

How We Can Locate Validatable Foundations of Life Themes
Jeremy Horne
(pages: 21-32)

Bringing Discipline into Transdisciplinary Communications -The ISO 56000 Family of Innovation Standards-
Rick Fernandez, William Swart
(pages: 33-39)

To AI Is Human: How AI Tools with Their Imperfections Enhance Learning
Martin Cwiakala
(pages: 40-46)

Knowledge, Learning and Transdisciplinary Communication in the Evolution of the Contemporary World
Rita Micarelli, Giorgio Pizziolo
(pages: 47-52)

Human Complexity vs. Machine Linearity: Tug-of-War Between Two Realities Coexisting in Precarious Balance
Paolo Barile, Clara Bassano, Paolo Piciocchi
(pages: 53-62)

A Cybernetic Metric Approach to Course Preparation
Russell Jay Hendel
(pages: 63-70)

The Impact of Artificial Intelligence on Education
John Jenq
(pages: 71-76)

Bridging the Gap: Harnessing the Power of Machine Learning and Big Data for Media Research
Li-jing Arthur Chang
(pages: 77-84)

Image Processing, Computer Vision, Data Visualization, and Data Mining for Transdisciplinary Visual Communication: What Are the Differences and Which Should or Could You Use?
Richard S. Segall
(pages: 85-92)

Identification – The Essence of Education
Jeremy Horne
(pages: 93-99)

The Greek-Roman Theatre in the Mediterranean Area
Maria Rosaria D’acierno Canonici Cammino
(pages: 100-108)

Examination of AI and Conventional Teaching Approaches in Cultivating Critical Thinking Skills in High School Students
Luis Castillo
(pages: 109-112)

Thoughts, Labyrinths, and Torii
Maurício Vieira Kritz
(pages: 113-119)

Can Two Human Intelligences (HIs or Noes) and Two Artificial Intelligences (AIs) Get Involved in Interlinguistic Communication? – A Transdisciplinary Quest
Ekaterini Nikolarea
(pages: 120-128)


 

Abstracts

 


ABSTRACT


Repurposeable Learning Objects Linked to Teaching and Learning Styles

Jeremy Dunning, Donald Cunningham, Larry Vandermolen, Tom Hunt, Ari Vidali, Abtar Kaur


Multimedia learning objects are an essential component of high quality, technology-mediated instruction. Learning objects allow the student to use the content learned in a particular part of a course and; 1. demonstrate mastery of the content, 2. apply that knowledge to solving a problem, and 3. use the content in a critical thinking exercise that both demonstrates mastery and allows the student to place the content within the context of the larger topic of the course. The difficulty associated with the use of learning objects on a broad scale is that they require programming skills most professors and instructors do not possess. Learning objects also tend to be custom productions and are defined in terms of the programming and code terminology, further limiting the professor’s ability to understand how they are created. Learning objects defined in terms of styles of learning and teaching allow professors and instructors to develop a deeper understanding of the learning objects and the design process.

A set of learning objects has been created that are designed for some of the important styles of learning and teaching. They include; visual learning, writing skills, critical thinking, time-revealed scenarios, case studies and empirical observation. The learning objects are designed and described in terms that the average instructor can readily understand , redesign and incorporate into their own courses. They are also designed in such a way that they can readily be repurposed for new applications in other courses and subject areas, with little or no additional programming.

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